0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessDevelopment and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although prosthetic hand devices with myoelectric control can be dated back to more than 70 years ago, their applications with anthropomorphic robotic mechanisms and sensory feedback functions are still at a relatively preliminary and laboratory stage. Nevertheless, a recent series of proof-of-concept studies suggest that soft robotics technology may be promising and useful in alleviating the design complexity of the dexterous mechanism and integration difficulty of multifunctional artificial skins, in particular, in the context of personalized applications. Here, we review the evolution of neuroprosthetic hands with the emerging and cutting-edge soft robotics, covering the soft and anthropomorphic prosthetic hand design and relating bidirectional neural interactions with myoelectric control and sensory feedback. We further discuss future opportunities on revolutionized mechanisms, high-performance soft sensors, and compliant neural-interaction interfaces for the next generation of neuroprosthetic hands.
Guoying Gu, Ningbin Zhang, Chen Chen, Haipeng Xu, Xiangyang Zhu (2023). Soft Robotics Enables Neuroprosthetic Hand Design. ACS Nano, 17(11), pp. 9661-9672, DOI: 10.1021/acsnano.3c01474.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
5
Datasets
0
Total Files
0
Language
English
Journal
ACS Nano
DOI
10.1021/acsnano.3c01474
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access